integrated urban water systems

8/17/2019 Integrated Urban Water Systems

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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

Vojinovic and Seyoum 1

Integrated urban water systems modelling with a simplified

surrogate modular approach

Z. Vojinovic1*, and S.D. Seyoum

2

Department of Hydroinformatics and Knowledge Management, UNESCO-IHE, Institute for Water Education,Westvest 7, 2611 AX Delft, The Netherlands

*Corresponding author, e-mail: [email protected]

ABSTRACTIn a complex urban environment, modelling tools are needed to describe the complex water-

related interactions, and to allow management strategies to be developed. Typically, two

types of models are used: simplified (or strategic) and detailed ones. Simplified models are

normally used for strategic planning purposes, whereas, detailed models are needed to

describe the system’s performance according to the specific local needs and objectives. This

paper addresses the issue of setting up conceptual modelling platform to replicate the larger

part of urban water cycle in order to evaluate different strategies and scenarios for integrated

urban water management at the planning level. It explores the use of integrated simplified

models in a procedure where the model parameters of these models are derived either fromthe measurements or from a detailed physically-based model results. The paper presents an

ongoing research work undertaken within the work package 1.2 of the EU funded SWITCH

project (further information about this project can be found at: www.switchurbanwater.eu).

Apart from the discussion of concepts of simplified integrated modelling, this paper also

presents some of the preliminary results obtained form a case study where an existing

simplified modeling system (CITY DRAIN) is used as a starting point to develop a more

comprehensive tool.

KEYWORDSUrban water systems; sewer systems; receiving waters; integrated modeling;

INTRODUCTIONIntegrated urban water management has emerged as an important concept for several reasons.

First, there is the growing need to manage the urban water cycle on a global basis. Second, a

range of alternative technologies to process different aspects of the urban water cycle are

becoming available. Third, advances in urban hydroinformatics enable different phases of

the entire cycle to be modeled and to use such models to optimise each phase locally and in

the global context. In particular, the advances in urban hydroinformatics have made

significant impacts on the development of new strategies for urban water management. The

use of computer models pervades all aspects of water management, supporting wealth

creation through products and services, contributing to many improvements in the quality of

life. As a result, there is a growing increase in demands for better use, productivity, flexibility,

robustness and quality of urban water modelling systems. In the urban water sector, no

serious investment decisions are being made without the use of computer models to evaluate

various scenarios. In this context, computer modelling of the urban water cycle is aimed at

understanding and predicting the behaviour and performance of the component and integrated

systems so that the effective solutions to structural and operational problems can be derived

and evaluated within a decision-making framework.

The paper presents some of the concepts for setting up the simplified integrated modelling

framework for integrated urban water systems modelling in order to evaluate different


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2 Integrated urban water systems modelling with a simplified surrogate modular approach

strategies and scenarios for integrated urban water management at the planning level. A brief

review of sewer component of a simplified modeling approach embedded within the CITY

DRAIN model is given followed by a case study where the main objective was to evaluate its

capabilities to be used as a platform for simplified integrated modeling purposes.

SIMPLIFIED INTEGRATED MODELLING

The need for integrated analysis has been discussed in literature (see for example, Rauch et al.1998; 2002) and it has also been formulated within the EU Water Framework Directive

60/2000 with a water-quality orientated view on the whole system which calls for new ways

of assessing its performance.

Models can be employed to meet many different objectives during the planning, design and

operation phase of urban water systems, and thus different types of models are needed to

correspond to different needs. Mathematical models in general can range from simple

equations to complex software codes including many equations and conditions over the time

and spatial domain.

Generally speaking, mathematical models used in urban water application are aimed at

facilitating various aspects such as planning, operations and design. Certainly, depending on

the purpose and objectives of the work different modeling approaches can be applied.

Typically, these approaches differ with respect to the level of complexity and sophistication

of equations used to describe the governing processes. The main difference in applying

different modelling approaches is the amount of data required, the information that can be

obtained from the model, the sophistication of the analysis performed and the simulation

period.

Although the basic principles are known, the development of integrated models is still a

challenging task. The main bottleneck is the complexity of the total system that prevents a simple

linkage of the existing physically based models of the individual subsystems to an entity (Rauch et

al, 2001). Another problem encountered when creating an integrated model is the fact that theexisting models are quite complex and require sophisticated integration algorithms to solve them.

This results in long calculation times, making these models impractical to use, especially within

optimisation problems where a lot of simulations need to be performed. Model integration is

also a challenging task due to the reasons related to data formats, compatibility of scales,

ability to modify source codes, etc. To overcome such difficulties, there are attempts by

commercial software companies to develop the links between different detailed physically-

based models (Moore et al, 2004) to enable development of integrated modeling platforms.

However, efforts in instantiating such models and their linking and running, which usually

takes a substantially long period of time, is still impractical for many applications especially

for those applications concerning strategic planning purposes where not only integration

between different components of urban water cycle is needed but also simulation of different

scenarios and optimization is necessary too.

What is therefore needed is the ability to undertake a holistic analysis of the urban water

cycle by setting up relatively simple models with reasonable accuracy. Due to the limitations,

which make detailed physically-based models based on the conservation of mass and

momentum, inefficient and impractical for integrated modelling for strategic planning

purposes, there is a need to replace such models by fast surrogate (an approximate substitute)

models and to link them up within the same platform. Implicit in this is a requirement both to


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understand and to be able to model not only the individual urban water processes but also

their interactions in a relatively simplified modeling framework (Figure 1).

G r o u n d w a t e r

W a t e r

t r e a t m e n t

D r i n k i n g w a t e r

d i s t r i b u t i o n

W W T P

Treatment

Reservoir

S e w e r

S y s t e m

Overflow

R e c i p i e n t

G r o u n d w a t e r

W a t e r

t r e a t m e n t

D r i n k i n g w a t e r

d i s t r i b u t i o n

W W T P

Treatment

Reservoir Reservoir

S e w e r

S y s t e m

OverflowOverflow

R e c i p i e n t

Figure 1. Schematisation of the urban water cycle and interactions between different

components.

Several researchers have attempted to respond to the challenge of developing simplified

integrate modeling. For example, the wastewater side of urban water cycle, which involvesinteraction between the sewer system, treatment plant and recipients has been described by

integrated urban wastewater modelling tools such as KOSIM-WEST (Solvi et al, 2005),

SIMBA (Freni et al, 2003), Cosmos (Calabro, 2001) and CITY DRAIN (Achleitner et. al.

2007). Such models use simplified conceptual hydrologic flow routing methods (for example,

in the case of CITY DRAIN Muskingum flow routing model was used) which might be

found more applicable for the routing of free surface flows and less applicable to the routing

of surcharged pipe network flows. Zoppou (2001) has emphasized the importance of

estimating urban flows accurately for integrated modelling for the reasons that pollutant

concentrations and loads cannot be estimated without having estimated the flows and also

procedures to mitigate quantity and quality are often complementary.

It is apparent from literature review of modelling tools for integrated urban wastewater

systems that, most of the modeling tools employed conceptual models to estimate the urban

flows due to the advantage they possess from a computational intensity point of view.

However, due to their conceptual nature, these models cannot provide accurate results

compared to the physically based models especially in conditions of surcharge flows, surface

flooding and significant backwater effect. Since the level of accuracy of the urban stormwater

modelling is fundamental to the overall accuracy of integrated urban water systems modelling,

for the development of simplified integrated urban water system model the emphasis should

be given to the ability of simulating urban drainage component as accurately as possible.

The conceptual model represents the hydrological processes that are seemingly important in

the system using a simplified, conceptual representation. To use these models for estimatingurban water flows, it is necessary to estimate the model parameters relevant to these systems.

The model parameters for gauged drainage systems are generally estimated by undertaking

either trial-and-error or an automatic calibration process. However, this is not possible for

ungauged systems due to the absence of rainfall and runoff data. If a form of equations which

can correlate model parameters to the drainage system characteristics can be derived, such

equations could be then used to estimate model parameters for ungauged drainage systems.

An attempt to develop such equations would be to derive a large number of model parameters

that correspond to a large number of gauged catchments via calibration process and then to


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derive a mapping function which can provide the parameter values for a given combination of

catchment characteristics. In some other cases where limited data (or measurements) exist an

approach would be to develop a physically-based model, calibrated it and generate the time

series data that could be used for derivation of parameters of a simplified model, Figure 2.

Similar methodology was applied by Meirlaen et al (2001) and it can be seen as a process of

transferring the knowledge contained within the physically based model into the conceptual

model by means of such virtual data.

The requirement for a strategic model is that it needs to be less complex and computationally

less expensive when compared to the physically-based models but still be able to produce

reasonably accurate outputs (or replicate the outputs of the deterministic models) for strategic

planning purposes. Setting up a simplified integrated urban water modelling framework can

be accomplished by the flowing steps: developing a conceptual model for each component of

urban water cycle, calibration based on observed data (or on virtual data generated by the

physically-based model) and integration between the simplified models of each component.

CONCEPTUAL SEWER MODELCurrently, a research has been being undertaken to develop a simplified modelling

framework with associated tools for strategic planning purpose under the EU funded

SWITCH project. In this research, the use of an open source model such as CITY DRAIN has

undertaken and some efforts have been made in testing the capability of such model to

replicate the behaviour of a physically based model. For this purpose the sewer component of

CITY DRAIN model is used to model urban sewer systems and results are compared to the

results of physically based model (in this case, the MOUSE modeling system, which is a

product developed by DHI Water & Environment was used). The intention here is to evaluate

strengths and weaknesses of a simplified modellling approach (such as the one embedded

within the equations of CITY DRAIN model) and to come up with plans for future

improvements in order to make such tool more useful for strategic planning purposes.

Figure 1. From Reality to Simplified Conceptual Models (Adopted from Meirlaen et al,

2001).

ExistingCatchment and

Sewer system

ExistingWastewater

Treatment Plant

Existing River(receiving water)

Physically Based

Catchment and

sewer model

Complex WWTP

Models

Physically Based

River Models

Data Collection

Data Generation

Reality

Simplified

Conceptual

Models

Physically Based

Models

Conceptual

Catchment andsewer model

Simplified

Conceptual

WWTP Model

Simplified

Conceptual

Model

Integrated Wastewater System


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CITY DRAIN is open source software developed for the purpose of integrated modelling of

urban drainage systems, Achleitner (2006). The model was developed within the

Matlab/Simulink © environment, enabling a block wise modelling of different parts of an

urban drainage system. The open source structure of the software allows for potential

addition of blocks and/or modification of existing blocks (and underlying models) according

to specific needs (Achleitner et al, 2007).

The computation in CITY DRAIN is based on a fixed discrete time step approach where each

subsystem uses the same time increment, usually predetermined by the temporal resolution of

the rainfall data used. Models implemented for hydraulics and mass transport are formulated

for a discrete time step Δt. A simple loss model is used to account for losses. Volume of

water that can be retained due to initial loss is represented by a basin. The volume of rain

exceeding the basin’s volume is considered to be the effective precipitation, contributing to

the catchment surface flow. Permanent losses such as evapotranspiration can be either

considered acting all the time or during dry weather only. The volume per time step to be

evaporated is limited by the initial loss specified. The Muskingum method is used for flow

routing in the catchment, sewer and river blocks. The system (catchment, channels andconduits) is considered as a whole. The model has separate blocks for handling the combinedand separate sewer systems. The model also has blocks for combined sewer overflow

structures and pumping stations. The hydraulic calculations for these structures are based on

the continuity equation and on maximum flow capacities. From this modeling approach, it

follows that pressurized flow, surface flooding and backwater effects cannot be modelled by

CITY DRAIN. It is our intention to improve the existing version of CITY DRAIN model to

account for such effects in a simplified way.

CASE STUDYThe sewer component of CITY DRAIN model was used to model urban catchments with

different characteristics. The model is manually calibrated and verified using data generated

by the MOUSE model. The results from a small urban catchment in Japan which covers anarea of about 35.43 hectares with population of 9004 inhabitants and with pipes diameter

ranging from 0.6m to 1.65m is shown here. This catchment has been subject to free surface

flow and surface flooding conditions. The calibration and verification for event based

simulation produced good fit to the data for free flow conditions; however, as expected the

model failed to produce meaningful results for surface flooding condition (Figure 3 and Table

1). For surface flooding condition, a retention basin was introduced within the CITY DRAIN

model in order to retain the flow, which exceeds the pipe full capacity of the outfall pipe.

Such alteration had improved the calibration and verification results. Table 1 shows the

values of coefficient of determination R 2 and the Nash-Sutcliffe efficiency E.

Table 1. Coefficient of determination R 2 and the Nash-Sutcliffe efficiency E for CITY

DRAIN model results.

Free flow condition Surface flow condition

R 2 Efficiency R

2 Efficiency

Calibration 0.99 0.99 0.95 0.95

Verification 0.88 0.87 0.90 0.89


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Event 2

0

0.4

0.8

1.2

1.6

2

19, 2:38 19, 3:50 19, 5:02 19, 6:14 19, 7:26 19, 8:38 19, 9:50

Time [day, hour:minute]

D i

s c h

a r g

e

[ m

3 / s ]

Mouse

CD

Calibration Verification

Event 2

0

2

4

6

8

10

12

14

19, 4:48 19, 6:00 19, 7:12 19, 8:24 19, 9:36

Time [day, hour:minute]

D i s c h a r g e [ m

3 / s ]

Mouse

CD

Calibration when there is surface flooding (with no retention basin provided)

Calibration (with retention basin included) Verification

Figure 3. Calibration and verification results for free flow and surface flooding conditions.

DISCUSSION

CITY DRAIN model provides several advantages and disadvantage compared to the physically-based models. The significant advantages are that it is easy to build and set up, its

data requirements are relatively less significant and its computational time is significantly

lower. The modular approach enables to represent a catchment in a semi-distributed way.

The parameters of the sewer component include the initial loss (mm), the permanent loss

(mm/day), the number of time steps and the Muskingum parameters K(s) and X. In the

calibration process overlapping effect of the parameters K and the number of steps has been

observed. As the number of subcatchments, combined overflow structures and pumping

Verification

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

14,12:00 14,13:12 14,14:24 14,15:36 14,16:48 14,18:00 14,19:12 14,20:24 14,21:36 14,22:48 15,00:00

Time [day, hr:minute]

D i s c h a r g e [ m

3 / s ]

MOUSE

CD


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stations increased, number of calibration parameters increase by many fold which makes the

process of manual calibration difficult.

CITY DRAIN model performed reasonably well for free flow conditions (with and without

surcharge) and in catchments with moderate to high slope. For surface flooding and surcharge

conditions and in flat catchments the model is not expected to produce reliable results owing

to its conceptual nature. The retention block introduced appeared to be a relatively effective

measure in order to replicate surcharge flow conditions.

CONCLUSIONFor the development of a simplified integrated modelling platform an existing tool CITY

DRAIN has been used as a starting point. For improvements of this tool, the emphasis has

been given to the development of algorithmic procedures which can better describe the

behavior of floods and overflow surcharges. The preliminary results suggest the potential of

such modeling approach to be used as a tool for strategic planning purposes. Issues for further

improvement of this model will include provision of an automated procedure for optimal

parameter estimation based on evolutionary algorithms, uncertainty assessment and provision

of methodology for estimation of model parameters for case of ungauged catchments. Also,further improvements will be also made towards better and more convenient graphical user

interface.

REFERENCES Achleitner, S., Möderl, M. and Rauch, W., (2007), CITY DRAIN © - An open source

approach for simulation of integrated urban drainage systems, Environmental Modelling

& Software, Volume 22, Issue 8, August 2007, 1184-1195.

Calabro P.S. (2001) Cosmoss: conceptual simplified model for sewer system simulation. A

new model for urban runoff quality. Urban Water, 3, 33–42

Freni G, Milina J, Maglionico M, DiFederico V (2003) State for the art in Urban Drainage

Modelling, CARE-S (EU project “CARE-S Computer Aided REhabilitation of Sewer

networks: Project Number EVK1-CT-2001-00167”), report D7, 2003Meirlaen J., Huyghebaert B., Sforzi, F. Benedetti L. and Vanrolleghem P., (2001), Fast,

simultaneous simulation of the integrated urban wastewater system using mechanistic

surrogate models, Water Science and Technology, Vol 43 No 7 pp 301–309

Moore R, Tindall and Fortune D, 2004, Update on the HamonIT project: The OpenMI

standard for model linking, Proceedings of the 6th International conference on

hydroinformatics, World scientific Publishing Company.

Rauch W., Bertrand-Krajewski J. L., Krebs P., Mark O., Schilling W., Schütze M. and

Vanrolleghem P. A., (2002), Deterministic modelling of integrated urban drainage

systems. Water Science and Technology, 45 (3),81-94.

Rauch, W., Aalderink, H., Krebs, P., Schilling, W., & Vanrolleghem, P., (1998),

Requirements for integrated wastewater models – driven by receiving water objectives,

Water Science Technology, 38(11), 97–104.

Solvi A.-M., Benedetti L., Gillé S., Schosseler P., Weidenhaupt A. and Vanrolleghem

P.A.(2005), Integrated urban catchment modelling for a sewer-treatment-river system,

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Zoppou, C. (2001). Review of urban storm water models. Environmental modelling and

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